AMT method with the economical and convenient superiority plays a key role in exploring the sandstone-type uranium deposits in China, which mainly meets to four problems such as the thickness of overlying strata, delineating the shape of the significant sand bodies, whether there are buried structures and knowing the basement relief. Exploring the sand body shape is the key one among such problems because sand body provides the room of uranium deposits and is the prerequisite for exploring uranium mineralization. Through an example of outlining the sandstone layer within the mudstone layers, the ability can be improved to recognize the electrical resistivity anomaly among the weak electrical property contrast by adjusting the inversion model’s scale. A route to deal with the problem was given by inverting different scale models followed by checking whether the anomalies of each inversion are reliable. Finally, the geo-electrical model was to be determined by comparing results of different scale model.
Up to 1980’s, natural source EM method had not been applied to shallow geophysical exploration, while the MT method acquiring below several hundred Hz natural EM signals was mainly developed. AMT (the natural-source audio- magnetotelluric method) has become a key geophysical exploration method in several decades.
With speedy development of miscro-computer and signal processing and emergence of the impedance tensor decomposition, the commercial AMT instruments become mature up to 1990s and are applied for different purposes. With the advantage of economy and convenience as well as the ability to explore shallow objects (less than 2000 meters), many users are attracted to apply AMT to different fields such as ore exploration, engineer surveying and looking for water resources, etc. The more applied, the more techniques were promoted. In the past decades, many researchers were focusing on forward and inversion techniques of EM problems and there were new algorithms, which resulted in the significance of the feasible 2D inversion algorithms in field practices. However, there is little focus on model making. There are only several articles discussing the model making, such as Wannamaker et al. (1985) [
In the late 20th century, China began to devote exploring and mining leachable stand-stone type uranium Deposits, which enhanced AMT application in this field. AMT method in exploring uranium deposit exploration can give information of four aspects, such as the thickness of overlying strata, delineating the shape of the significant sand bodies, whether there are buried structures and knowing the basement relief. Uranium deposits exist in Erlian basin, the petroleum producer in northern China. Nuheting uranium deposit was discovered many years ago, but several other uranium deposits were found in recent years. To update exploring techniques and extend the area of uranium deposits, CNNC initiated Enlarging Uranium Resource and Evaluation technology Research for Building Mining Base project in 2010, which included several basins such as Erlian basin. Many new geophysical and geological data were acquired in this project to improve understanding geological units setting and determining new uranium deposits. An AMT profile (YC profile) was recorded in 2014, locating at the eastern Erlianhot and the northern Ulanqab depression (
The particular aims of this paper are to present an AMT application of recognizing sandstone body in the weak resistivity contrast at Erlian basin of China and to give an AMT data inverting route to deal with the problem in such situation.
Erlian basin was meso-cenozoic inland basin developed in Tianshan-Mongolia- Xingan Variscan fold belts, which are the south-east margin of the Central Asia Mongolia geosynclinals fold belt.
Basin base is composed of the Proterozoic or Paleozoic metamorphic rock series and intermediate acid intrusive rocks of Variscan and Yanshan period. The cover of this basin is mainly comprised of Cretaceous formation, which includes
Aershan formation (K1a), Tenggeer formation (K1t), Saihan formation (K1s) and Erlain formation (K2e) from bottom to top. The major tectonic line is in E-W direction.
Aershan formation (K1a) was composed of coarse detrital sedimentary formed in stage of strongly pulling apart The rocks of the lower Tegeer formation are pebbled sandstone, or siltstones with mudstone, while the upper’s are mudstones. The rocks of Saihan formation are sandstones intercalated by mudstones, lignite or pebbly mudstones with sandstones and the sandstones of this formation provided the room of uranium ore-bodies. The rocks of the lower Erlian formation are sandy conglomerates, sandstone or mudstone and so on, while the upper’s are mudstones.
There is the borehole E14-7 at a distance 9200 m on the profile, and its well logging resistivity curve and lithological column are plotted in
A 27-km long YC profile in NNW direction (
with V8 multi-function receiver the AMTC-30 induction coils of Phoenix Geophysics Limited.
The AMT station space is 100 meters and the electrode spacing is 50 meters with tensor layout using non polarized electrodes. Little human interference is conducive to AMT data recording. In order to further improve data quality, each station’s data were recorded for over 25 minutes.
The first step to process the AMT data is to convert each station’s time serial data to the frequency domain before calculating the cross power spectrum. Then, the estimation of each station’s impedance is followed by seeking a corresponding resistivity model which also satisfies a specified regularization function through inversion. The time serial data stacked by long time recording provide plenty of geo-electric field information. The impedance of each station is estimated through the robust method by TSP program’s kernel [
Developed by Randy Mackie, Inversion software (WinGLink®) finds regularized
solutions (Tikhonov Regularization) to the two-dimensional inverse problem for magnetotelluric data using the method of nonlinear conjugate gradients (William, etc., 2001) [
There is a difference between the inverted geo-electrical model (
WinGLink. Then, projecting this resistivity distribution to a fine mesh produced from a coded program and inverting it. The thinking of this program is similar to the route of producing a fine mesh of the WinGLink software. However, there are significant differences between them especially at the algorithm. The height or width of a cell can be set respectively, and there are no more adding elements beyond the maximum detecting depth calculated from the whole data. Trial and error approach is used to balance total element number and model scale, while ensuring that cells are kept sufficiently fine for accurate numerical calculation. By inverting YC profile AMT data with a new model produced by this method, a new geo-electrical model was obtained in the
There is a resistivity layer near the depths from 165 m to 275 m in
There is a clear bias between the constrained model and unconstrained model from the observed curves. There is a resistivity anomaly layer exiting at the depths from 165 m to 275 m near the borehole indeed.
Studying key sandstone body’s shape is a key task for exploring the leachable sandstone type uranium deposits, for the sandstone body is the room where the ore may exist. Many sandstone bodies are surrounded by the conductive mudstone layers, which add the difficulty in exploring such sandstone bodies. Especially, the low resistivity contrast adds the difficulty in imaging such anomaly.
The analysis above shows that the sandstone layer or body (a little higher resistivity layer), which agrees with the well logging data and is within the conductive layers, was imaged through adjusting the model’s scale by the identical inversion algorithm. It’s inferred that the different scale the models indeed influenced the result of the inversion and adjusting model’s scale to invert data are a key step for AMT data inversion especially in such little contrast environment. So, it’s recommended to calculate more times with two steps to meet such situation. The first step is to invert different scale models, then to check the anomalies of each inversion by the above way or the known information. This inversion route can defend missing some anomalies hidden in the data, especially for the weak resistivity contrast condition.
Yao, S.C., Wang, M., Duan, S.X., Chen, S., Liu, W.S. and Xu, D.L. (2017) Exploring Sandstone Body in Weak Electrical Resistivity Contrast with AMT Data. International Journal of Geosciences, 8, 277-285. https://doi.org/10.4236/ijg.2017.83012